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Spatially explicit modeling of parking search as a tool for urban parking facilities and policy assessment

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  • Levy, Nadav
  • Render, Marc
  • Benenson, Itzhak

Abstract

The engineering view of a measurable, supply-independent, demand for parking that can be expressed by “minimum parking codes” has been generally rejected during the last two decades and is gradually being replaced by “maximum provision” codes, limited parking development, and demand pricing. To assess new planning practices one has to estimate the drivers' reaction to proposed spatial–temporal parking limitations. The paper applies a high-resolution spatially explicit agent-based model termed “PARKAGENT” as a tool for this assessment. The model is used for evaluation of parking demand in the Diamond Exchange area in Ramat Gan, a city in the Tel Aviv metropolitan area, for estimating the effectiveness of planned parking facilities for different development scenarios in the area and assessing electronic signage system that directs drivers to vacant parking lots. The results strongly indicate the advantages of agent-based modeling over the current dominant engineering approach and show the potential benefits of using an intelligent parking guidance system.

Suggested Citation

  • Levy, Nadav & Render, Marc & Benenson, Itzhak, 2015. "Spatially explicit modeling of parking search as a tool for urban parking facilities and policy assessment," Transport Policy, Elsevier, vol. 39(C), pages 9-20.
    • Handle: RePEc:eee:trapol:v:39:y:2015:i:c:p:9-20
    DOI: 10.1016/j.tranpol.2015.01.004
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    References listed on IDEAS

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    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Premaratne Samaranayake & Upul Gunawardana & Michael Stokoe, 2023. "Kerbside Parking Assessment Using a Simulation Modelling Approach for Infrastructure Planning—A Metropolitan City Case Study," Sustainability, MDPI, vol. 15(4), pages 1-24, February.
    2. Levy, Nadav & Benenson, Itzhak, 2015. "GIS-based method for assessing city parking patterns," Journal of Transport Geography, Elsevier, vol. 46(C), pages 220-231.
    3. Assemi, Behrang & Baker, Douglas & Paz, Alexander, 2020. "Searching for on-street parking: An empirical investigation of the factors influencing cruise time," Transport Policy, Elsevier, vol. 97(C), pages 186-196.
    4. Juste Rajaonson & Georges A. Tanguay, 2019. "Urban Sustainability Indicators from a Regional Perspective: Lessons from the Montreal Metropolitan Area," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 141(3), pages 985-1005, February.
    5. Chaniotakis, Emmanouil & Pel, Adam J., 2015. "Drivers’ parking location choice under uncertain parking availability and search times: A stated preference experiment," Transportation Research Part A: Policy and Practice, Elsevier, vol. 82(C), pages 228-239.
    6. Gu, Ziyuan & Safarighouzhdi, Farshid & Saberi, Meead & Rashidi, Taha H., 2021. "A macro-micro approach to modeling parking," Transportation Research Part B: Methodological, Elsevier, vol. 147(C), pages 220-244.
    7. Juan Li & Jing Ye & Qinglian He & Chunfu Shao, 2016. "A Novel Scheme to Relieve Parking Pressure at Tourist Attractions on Holidays," Sustainability, MDPI, vol. 8(2), pages 1-11, February.

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